2010
DOI: 10.1007/s00170-009-2484-y
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An improved mesh simplification method using additional attributes with optimal positioning

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Cited by 7 publications
(9 citation statements)
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“…Shu et al introduced a two stage adaptive triangular mesh coarsening [33]. Choi et al presented a feature sensitive simplification method using curvature color [9]. Morigi and Rucci used a multi-level simplification preserving the original topology with good approximation gain to the original geometry [23].…”
Section: Related Workmentioning
confidence: 99%
“…Shu et al introduced a two stage adaptive triangular mesh coarsening [33]. Choi et al presented a feature sensitive simplification method using curvature color [9]. Morigi and Rucci used a multi-level simplification preserving the original topology with good approximation gain to the original geometry [23].…”
Section: Related Workmentioning
confidence: 99%
“…Various methods have been proposed for mesh simplification, and these can be divided into three main categories: vertex decimation, vertex clustering, and iterative edge contraction [5][6][7][8][18][19][20]. Vertex decimation methods involve three major steps: selection of candidate vertexes that satisfy a distance or an angle criterion, removal of loop triangles around the candidate vertexes, and triangulation of the resulting holes [9,18,[20][21][22].…”
Section: Related Workmentioning
confidence: 99%
“…Although these methods are time-efficient, the candidate vertex selection criterion is based on a local error estimate and therefore cannot guarantee the boundary errors. Moreover, they can only preserve positions, and few salient features are preserved during simplification [7,19,22].…”
Section: Related Workmentioning
confidence: 99%
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“…Surface mesh simplification has been given a lot of attention. We are interested in methods considering geometry and aspect-describing attributes (e.g., color, texture) [3,4,[7][8][9]11,12]. Methods exploiting the unitary edge collapse operation ( Fig.…”
Section: Mesh Simplificationmentioning
confidence: 99%